The local refractive power or the refractive power distribution of a spectacle lens is measured. A first image of a scene having a plurality of structure points and a left and/or a right spectacle lens of a frame front is captured with an image capturing device from a first capture position having an imaging beam path for structure points, which extends through the spectacle lens of the frame front. At least two further images of the scene are captured with the image capturing device from different capture positions, one of which can be identical with the first capture position, without the spectacle lenses of the spectacles or without the frame front containing the spectacle lenses having the structure points imaged in the first image, and the coordinates of the structure points in a coordinate system are calculated from the at least two further images of the scene by image analysis.
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2. The method as claimed in claim 1, wherein the image evaluation is implemented by an object recognition method.
This invention relates to image evaluation systems, specifically methods for analyzing images to detect and recognize objects within them. The technology addresses the challenge of accurately identifying and classifying objects in digital images, which is crucial for applications such as autonomous vehicles, surveillance, and quality control in manufacturing. The method involves using an object recognition technique to evaluate images. Object recognition is a computer vision process that identifies and classifies objects within an image by analyzing patterns, shapes, and features. The system processes the input image to detect objects, then applies recognition algorithms to determine what those objects are. This may include techniques like convolutional neural networks, template matching, or feature-based detection, depending on the application. The method ensures that the image evaluation is performed using a specialized object recognition approach, enhancing accuracy and reliability in identifying objects. This is particularly useful in scenarios where precise object detection is critical, such as in automated inspection systems or real-time monitoring applications. The system may also include preprocessing steps like noise reduction or contrast enhancement to improve recognition performance. By leveraging object recognition, the method provides a robust solution for automated image analysis, reducing the need for manual intervention and improving efficiency in various industrial and consumer applications.
3. The method as claimed in claim 1, further comprising capturing a multiplicity of first image representations of the scene and a multiplicity of further image representations of the scene, wherein the coordinates of the at least one structure point in the coordinate system which is referenced to the coordinate system of the spectacle frame are calculated from the multiplicity of further image representations of the scene.
This invention relates to a method for determining the position of a structure point in a scene relative to a spectacle frame. The method addresses the challenge of accurately mapping points in a scene to a coordinate system referenced to a spectacle frame, which is critical for applications such as eyewear fitting, optical measurements, or augmented reality alignment. The method involves capturing multiple image representations of the scene from different perspectives to enhance precision. A first set of image representations is used to establish an initial reference, while a second set of further image representations is processed to refine the coordinates of at least one structure point in the scene. By analyzing the multiplicity of further images, the method calculates the precise coordinates of the structure point relative to the spectacle frame's coordinate system. This approach improves accuracy by leveraging redundant data from multiple images, reducing errors caused by single-image distortions or misalignments. The method is particularly useful in scenarios requiring high-precision spatial mapping, such as custom eyewear design or optical calibration systems. The use of multiple image captures ensures robustness against environmental variations and measurement inaccuracies, providing a reliable solution for aligning scene points with a spectacle frame's coordinate system.
4. The method as claimed in claim 1, wherein the scene contains a left eye and/or right eye of a spectacle wearer of the spectacle frame.
This invention relates to a method for analyzing a scene captured by a camera, particularly for applications involving spectacle frames and eyewear. The method addresses the challenge of accurately detecting and processing specific features within a captured image, such as the eyes of a spectacle wearer, to improve fitting, alignment, or other optical adjustments. The method involves capturing an image of a scene that includes at least one of the left or right eye of a person wearing a spectacle frame. The captured image is then processed to identify and analyze the eye(s) within the scene. This may involve detecting the position, orientation, or other characteristics of the eyes relative to the spectacle frame. The method may also include additional steps such as determining the fit of the frame, adjusting optical parameters, or verifying alignment. The technique is particularly useful in automated eyewear fitting systems, where precise detection of eye positions is critical for ensuring proper lens alignment and comfort. By focusing on the eyes within the scene, the method enhances the accuracy of measurements and adjustments, leading to better-fitting and more effective spectacle frames. The approach may be integrated into optical measurement devices, virtual try-on systems, or other applications requiring precise eyewear analysis.
5. The method as claimed in claim 4, wherein the image capture device captures a multiplicity of image representations of the scene with a displacement of the image capture device, wherein the left eye and/or the right eye of the wearer of the spectacle frame gazes at the displaced image capture device, wherein respective viewing beam paths for different viewing directions of the left eye and/or right eye of the wearer of the spectacle frame through the left spectacle lens and/or the right spectacle lens of the spectacle frame are calculated from the multiplicity of image representations of the scene, and wherein the local refractive power of the left spectacle lens and/or the right spectacle lens is determined for each viewing direction therethrough.
This invention relates to a method for determining the refractive power of spectacle lenses in a spectacle frame, particularly for personalized eyewear. The problem addressed is the need to accurately measure how light passes through lenses for different viewing angles, ensuring optimal vision correction for the wearer. The method involves capturing multiple images of a scene using an image capture device that is displaced relative to the spectacle frame. The wearer's left and/or right eye gazes at the displaced device during this process. By analyzing the captured images, the system calculates the viewing beam paths for different directions of the wearer's gaze through the left and/or right spectacle lens. These calculations account for how the lenses refract light as the wearer looks in various directions. The local refractive power of each lens is then determined for each viewing direction, providing a detailed map of how the lenses correct vision across the entire field of view. This approach ensures precise lens customization, addressing variations in refractive power that occur when the wearer shifts their gaze. The method is particularly useful for progressive lenses or other complex lens designs where refractive power varies across the lens surface.
6. The method as claimed in claim 1, wherein intrinsic parameters of the at least one image capture device are calculated with a Simultaneous Localization and Mapping (SLAM) algorithm.
This invention relates to computer vision and augmented reality systems, specifically improving the accuracy of spatial mapping and object tracking by dynamically calculating intrinsic camera parameters using a Simultaneous Localization and Mapping (SLAM) algorithm. The problem addressed is the reliance on pre-calibrated camera parameters, which can degrade performance due to environmental changes, sensor drift, or manufacturing variations. By integrating SLAM, the system continuously estimates and refines intrinsic parameters such as focal length, principal point, and lens distortion coefficients in real-time. This adaptive calibration enhances tracking stability and reduces errors in augmented reality overlays, robot navigation, or 3D reconstruction tasks. The method leverages feature detection and optimization techniques within the SLAM framework to iteratively adjust parameters based on observed scene geometry, ensuring consistent accuracy without manual recalibration. This approach is particularly useful in dynamic environments where traditional calibration methods fail, improving reliability for applications like autonomous vehicles, AR/VR devices, and industrial automation. The system may also incorporate multiple image capture devices, with each device's parameters independently or collaboratively refined to maintain synchronization and spatial coherence.
7. The method as claimed in claim 6, wherein the intrinsic parameters are selected from the group of a focal length, an image center, shearing parameters, scaling parameters, and distortion parameters.
This invention relates to camera calibration techniques, specifically methods for determining intrinsic camera parameters that define the geometric properties of an imaging system. The problem addressed is the need for accurate and efficient calibration of cameras to correct distortions and ensure precise image mapping, which is critical for applications such as computer vision, robotics, and augmented reality. The method involves selecting intrinsic parameters that characterize the camera's optical behavior. These parameters include focal length, which determines the magnification of the lens; image center, representing the principal point where the optical axis intersects the image plane; shearing parameters, accounting for deviations in pixel alignment; scaling parameters, reflecting differences in pixel dimensions along the x and y axes; and distortion parameters, correcting for lens distortions like radial and tangential aberrations. By adjusting these parameters, the method enables precise calibration of the camera, ensuring accurate image rectification and reliable geometric measurements. The approach improves upon existing calibration techniques by systematically identifying and refining these key parameters, leading to more accurate and robust camera models. This is particularly useful in applications requiring high-precision imaging, such as 3D reconstruction, autonomous navigation, and machine vision systems. The method ensures that the camera's intrinsic properties are properly accounted for, minimizing errors in subsequent image processing tasks.
8. The method as claimed in claim 1, wherein a SLAM algorithm is used to calculate the coordinates of the at least one structure point and/or the recording positions of the at least one image capture device in the coordinate system, which is referenced to the coordinate system of the spectacle frame.
This invention relates to a method for determining the spatial relationship between a spectacle frame and at least one structure point or image capture device using a Simultaneous Localization and Mapping (SLAM) algorithm. The method addresses the challenge of accurately mapping and positioning components in a three-dimensional space, particularly in applications involving optical devices like spectacle frames. The SLAM algorithm processes data from one or more image capture devices to dynamically construct a map of the environment while simultaneously tracking the devices' positions relative to the spectacle frame. The algorithm calculates the coordinates of structure points (e.g., reference markers or features on the frame) and the recording positions of the image capture devices within a coordinate system aligned with the spectacle frame. This enables precise spatial localization, which is critical for applications such as frame fitting, alignment, or augmented reality integration. The method ensures real-time or near-real-time updates of the coordinate data, allowing for dynamic adjustments as the frame or devices move. The SLAM-based approach improves accuracy over traditional methods by continuously refining the map and position estimates using sensor data. This technique is particularly useful in scenarios where manual measurements are impractical or where high precision is required, such as in custom spectacle manufacturing or vision correction systems.
9. The method as claimed in claim 1, wherein the coordinates of at least some of the structure points in the scene are invariant.
This invention relates to a method for processing three-dimensional (3D) scene data, particularly for applications in computer vision, robotics, or augmented reality. The method addresses the challenge of accurately reconstructing or analyzing 3D scenes where certain structural points remain invariant, meaning their coordinates do not change over time or under different conditions. These invariant points can serve as stable reference points for tasks such as object tracking, scene mapping, or spatial localization. The method involves capturing or generating a 3D representation of a scene, which includes a set of structure points defining the geometry of objects or surfaces within the scene. At least some of these structure points are identified as invariant, meaning their positions in the coordinate system remain constant. The method may use techniques such as feature matching, geometric constraints, or machine learning to detect and track these invariant points across multiple frames or observations. By leveraging these stable points, the method improves the accuracy and robustness of 3D scene reconstruction, object recognition, or motion estimation in dynamic environments. The invariant points can be used to align or register different views of the scene, correct for camera motion, or enhance the precision of depth sensing. This approach is particularly useful in scenarios where parts of the scene are subject to changes, such as moving objects or varying lighting conditions, while other parts remain static. The method may also incorporate additional techniques, such as filtering or optimization, to refine the coordinates of the invariant points and ensure consistency in the 3D model.
10. The method as claimed in claim 1, wherein the coordinates of at least one structure point are calculated in a coordinate system, which is referenced to the coordinate system of the spectacle frame, by evaluating displacements between the image representations of the structure points in the scene from different recording positions.
This invention relates to a method for determining the spatial coordinates of structure points on a spectacle frame or related objects in a three-dimensional coordinate system. The method addresses the challenge of accurately mapping the positions of key points on a spectacle frame, which is essential for tasks such as custom lens fitting, frame alignment, or digital modeling. The core problem is obtaining precise spatial coordinates of these structure points relative to the spectacle frame's coordinate system, which is necessary for applications requiring high accuracy, such as optical measurements or manufacturing. The method involves capturing multiple images of the spectacle frame from different recording positions. These images contain representations of the structure points, which may include frame edges, hinges, or other reference points. By analyzing the displacements of these image representations across the different views, the method calculates the three-dimensional coordinates of the structure points. The displacements are evaluated to determine the relative positions of the points in space, which are then referenced to the spectacle frame's coordinate system. This approach leverages multi-view imaging to enhance accuracy and reliability in coordinate determination, ensuring that the spatial relationships between the structure points and the frame are precisely defined. The method is particularly useful in automated or semi-automated systems where manual measurement is impractical or less accurate.
11. The method as claimed in claim 1, wherein a displacement of the structure points in the coordinate system is recognized by evaluating proximity relations between the structure points in the scene, and wherein the coordinates of structure points displaced in the scene are not taken into account when determining the refractive power distribution for the at least one section of the right spectacle lens and/or the left spectacle lens.
This invention relates to methods for determining the refractive power distribution in spectacle lenses, particularly for correcting vision in dynamic or changing environments. The problem addressed is ensuring accurate lens design when the positions of reference points (structure points) in a scene shift due to movement or other factors, which can lead to errors in refractive power calculations. The method involves analyzing the spatial relationships (proximity relations) between structure points in the scene to detect displacements. When a displacement is identified, the coordinates of the affected structure points are excluded from the refractive power distribution calculations for the right and/or left spectacle lens. This ensures that only stable, reliable reference points are used, improving the accuracy of the lens design. The underlying process involves capturing a scene with structure points, determining their initial coordinates, and then monitoring changes in their positions. By evaluating proximity relations—such as distances or relative positions—between points, the system detects when a point has moved. Displaced points are then ignored in subsequent calculations for the lens sections, preventing distortions in the refractive power distribution. This approach is particularly useful in applications where environmental or user movement could otherwise compromise lens accuracy.
12. A method for measuring a refractive power distribution of a left and/or a right spectacle lens in a spectacle frame, wherein the local refractive power of the left and/or right spectacle lens is measured according to the method as claimed in claim 1 at a plurality of different locations on the left and/or right spectacle lens.
This invention relates to measuring the refractive power distribution of spectacle lenses (left and right) mounted in a spectacle frame. The method addresses the challenge of accurately determining the local refractive power at multiple points across the lens surface, which is essential for verifying lens quality, fitting, and optical performance. The process involves measuring the local refractive power of the left and/or right lens at numerous distinct locations. This is achieved by analyzing the lens's optical properties at each measurement point, ensuring comprehensive coverage of the lens surface. The technique accounts for variations in refractive power across the lens, which can arise from design features such as progressive, multifocal, or aspheric corrections. By mapping these variations, the method provides a detailed refractive power distribution, enabling precise assessment of the lens's optical performance in its final mounted state. The approach is particularly useful for quality control in ophthalmic lens manufacturing and fitting, ensuring that lenses meet prescribed specifications and perform as intended when worn. The method can be applied to both single-vision and complex multifocal lenses, offering a versatile solution for optical verification.
13. A non-transitory computer program product comprising a computer program having program code for carrying out the method as claimed in claim 1 when the computer program is loaded on a computer unit and/or executed on the computer unit.
The invention relates to a computer program product for managing and executing a method to optimize data processing in a distributed computing environment. The method involves analyzing a data processing task to identify dependencies between subtasks, then dynamically allocating computational resources to minimize processing time while ensuring efficient resource utilization. The system monitors resource availability in real-time and adjusts allocations based on workload demands, prioritizing critical subtasks to prevent bottlenecks. It also includes error detection and recovery mechanisms to handle failures without disrupting the overall workflow. The computer program product stores this method in a non-transitory form, allowing it to be loaded onto a computer system for execution. The program code includes instructions for task decomposition, resource allocation, real-time monitoring, and adaptive scheduling, ensuring efficient and reliable data processing across distributed systems. The solution addresses inefficiencies in traditional distributed computing by dynamically optimizing resource allocation and task prioritization, reducing processing delays and improving system reliability.
14. A portable non-transitory computer-readable data medium, on which the computer program as claimed in claim 13 is stored.
A portable non-transitory computer-readable data medium stores a computer program designed to analyze and process data from a plurality of sensors. The program includes instructions for receiving sensor data, identifying patterns or anomalies within the data, and generating alerts or reports based on the analysis. The data medium is portable, allowing the program to be easily transferred or installed on different computing devices. The program may also include modules for data visualization, predictive modeling, or integration with external systems. The stored program is configured to operate on various computing platforms, ensuring compatibility across different devices. The data medium may be a USB drive, SD card, or other portable storage device. The program's functionality enables real-time or batch processing of sensor data, supporting applications in industrial monitoring, environmental sensing, or healthcare diagnostics. The stored program may also include user interfaces for configuring analysis parameters or viewing results. The data medium ensures the program can be deployed in environments where internet connectivity is limited or unavailable. The program's modular design allows for updates or additional features to be added without requiring a complete reinstallation. The stored program may also include encryption or security features to protect sensitive data during storage or transmission. The data medium provides a reliable way to distribute and execute the sensor data analysis program across multiple devices.
16. The apparatus as claimed in claim 15, wherein the apparatus is configured as a smartphone, a tablet computer, or as a camera.
This invention relates to a portable electronic device with enhanced imaging capabilities. The device includes a camera module with a lens system and an image sensor, along with a processing unit that analyzes captured images to detect and correct distortions, such as lens aberrations or geometric distortions. The processing unit also applies image enhancement techniques, including noise reduction, color correction, and dynamic range adjustment, to improve image quality. Additionally, the device may incorporate machine learning algorithms to optimize settings based on environmental conditions or user preferences. The apparatus can be configured as a smartphone, tablet computer, or standalone camera, ensuring versatility across different form factors. The system may also include a display for real-time preview and user interaction, along with input controls for manual adjustments. The invention addresses the need for high-quality imaging in portable devices by integrating advanced computational photography techniques into compact, user-friendly designs.
19. The method as claimed in claim 18, wherein the image evaluation is implemented by triangulation.
This invention relates to image evaluation techniques, specifically for determining spatial relationships or measurements within a captured image. The method addresses the challenge of accurately assessing distances, positions, or dimensions in an image, particularly when depth or three-dimensional information is needed. The core technique involves triangulation, a geometric method used to calculate distances or positions based on angles and known reference points. In this context, triangulation is applied to image data to derive precise spatial measurements. The method may involve capturing multiple images from different perspectives or using known reference markers within the image to establish a baseline for triangulation calculations. By analyzing the angles and intersections formed by these reference points, the system can determine the relative positions of objects or features within the scene. This approach is particularly useful in applications such as 3D reconstruction, robotics, autonomous navigation, or quality control in manufacturing, where accurate spatial data is essential. The triangulation-based evaluation enhances the accuracy and reliability of image-derived measurements compared to simpler methods, enabling more precise applications in various technical fields.
20. The method as claimed in claim 18, further comprising capturing a multiplicity of first image representations of the scene and a multiplicity of further image representations of the scene, wherein the coordinates of the at least one structure point in the coordinate system which is referenced to the coordinate system of the spectacle frame are calculated from the multiplicity of further image representations of the scene.
This invention relates to a method for capturing and processing images of a scene to determine the coordinates of at least one structure point in a coordinate system referenced to a spectacle frame. The method addresses the challenge of accurately mapping structural points within a scene, particularly in applications such as optical measurements or 3D modeling where precise spatial referencing is required. The method involves capturing multiple first image representations of the scene and multiple further image representations of the same scene. The coordinates of the structure point(s) are calculated using the further image representations, which are referenced to the coordinate system of the spectacle frame. This approach enhances accuracy by leveraging multiple image captures to refine the positional data of the structure points. The method may also include determining the position of the spectacle frame relative to the scene, ensuring that the coordinate system of the spectacle frame is properly aligned with the scene's coordinate system. Additionally, the method may involve calculating the position of the spectacle frame relative to the scene based on the first image representations, further improving the precision of the coordinate mapping. The use of multiple image captures allows for redundancy and error correction, ensuring reliable and accurate spatial measurements. This technique is particularly useful in applications requiring high-precision spatial referencing, such as optical measurements, 3D modeling, or medical imaging.
21. The method as claimed in claim 18, wherein the scene contains a left eye and/or right eye of a spectacle wearer of the spectacle frame.
This invention relates to methods for analyzing or processing scenes captured by imaging systems, particularly for applications involving spectacle frames and eyewear. The method involves capturing an image of a scene that includes at least one of the left or right eye of a spectacle wearer, where the spectacle frame is part of the scene. The system processes the captured image to detect and analyze the eye(s) and the spectacle frame, enabling applications such as eyewear fitting, gaze tracking, or virtual try-on. The method may include steps to identify the position, orientation, or fit of the spectacle frame relative to the wearer's eyes, ensuring proper alignment and comfort. Additionally, the system may adjust or optimize the spectacle frame's design based on the detected eye positions, improving the wearer's visual experience. The invention addresses challenges in accurately capturing and analyzing eyewear and eye positions in real-world scenarios, providing a more precise and automated solution for eyewear-related applications.
22. The method as claimed in claim 21, wherein the image capture device captures a multiplicity of image representations of the scene with a displacement of the image capture device, wherein the left eye and/or the right eye of the wearer of the spectacle frame gazes at the displaced image capture device, wherein respective viewing beam paths for different viewing directions of the left eye and/or right eye of the wearer of the spectacle frame through the left spectacle lens and/or the right spectacle lens of the spectacle frame are calculated from the multiplicity of image representations of the scene, and wherein the local refractive power of the left spectacle lens and/or the right spectacle lens is determined for each viewing direction therethrough.
This invention relates to a method for determining the local refractive power of spectacle lenses in a spectacle frame, addressing the challenge of accurately measuring how lenses refract light for different viewing directions. The method involves capturing multiple image representations of a scene using an image capture device that is displaced relative to the spectacle frame. During this process, the wearer's left and/or right eye gazes at the displaced image capture device. The system calculates the respective viewing beam paths for different viewing directions of the left and/or right eye through the left and/or right spectacle lens. By analyzing these beam paths from the captured images, the local refractive power of the lenses is determined for each viewing direction. This approach enables precise mapping of refractive properties across the entire lens surface, ensuring optimal vision correction for various gaze angles. The method leverages the displacement of the image capture device and the wearer's gaze to derive accurate refractive measurements, improving the customization and performance of spectacle lenses.
23. The method as claimed in claim 18, wherein intrinsic parameters of the at least one image capture device are calculated with a SLAM algorithm.
This invention relates to computer vision and simultaneous localization and mapping (SLAM) techniques, specifically for improving the accuracy of image capture devices in dynamic environments. The problem addressed is the need for precise calibration of intrinsic parameters (e.g., focal length, lens distortion) of image capture devices, such as cameras, to ensure accurate 3D reconstruction and localization in real-time applications like augmented reality, robotics, and autonomous navigation. The method involves using a SLAM algorithm to dynamically compute the intrinsic parameters of one or more image capture devices. SLAM algorithms typically track camera motion and map the environment by analyzing sequential images. By integrating intrinsic parameter estimation into the SLAM process, the system can adapt to changes in camera settings or environmental conditions without requiring manual calibration. This approach enhances robustness, as it continuously refines parameters like focal length and distortion coefficients based on real-time image data, reducing errors in 3D mapping and object tracking. The method may also involve using multiple image capture devices, where the SLAM algorithm synchronizes their intrinsic parameters to maintain consistency across different viewpoints. This is particularly useful in multi-camera setups, such as stereo or omnidirectional vision systems, where accurate parameter alignment is critical for depth estimation and scene reconstruction. The dynamic calibration process ensures that the system remains accurate even if cameras are moved or adjusted during operation, improving reliability in applications requiring high precision.
24. The method as claimed in claim 23, wherein the intrinsic parameters are selected from the group of a focal length, an image center, shearing parameters, scaling parameters, and distortion parameters.
This method determines the local refractive power of a spectacle lens. It works by capturing images of a scene containing at least a section of the spectacle lens using an image capture device. These images are then evaluated to calculate the coordinates of various structural points within the scene, with these coordinates referenced to the spectacle frame's coordinate system. The local refractive power of the lens section is then derived from these calculated structure point coordinates. Specifically, a Simultaneous Localization and Mapping (SLAM) algorithm is employed to calculate the intrinsic parameters of the image capture device. These critical parameters, which describe the camera's internal geometry, include its focal length, the image center, shearing parameters, scaling parameters, and distortion parameters. ERROR (embedding): Error: Failed to save embedding: Could not find the 'embedding' column of 'patent_claims' in the schema cache
25. The method as claimed in claim 18, wherein a SLAM algorithm is used to calculate the coordinates of the at least one structure point and/or the recording positions of the at least one image capture device in the coordinate system, which is referenced to the coordinate system of the spectacle frame.
This invention relates to a method for determining the spatial relationship between a spectacle frame and at least one structure point in a coordinate system referenced to the spectacle frame. The method addresses the challenge of accurately mapping the position of structure points, such as anatomical landmarks or reference markers, relative to a spectacle frame during fitting or adjustment processes. A Simultaneous Localization and Mapping (SLAM) algorithm is employed to calculate the coordinates of the structure points and the recording positions of at least one image capture device within the coordinate system tied to the spectacle frame. The SLAM algorithm enables real-time tracking and mapping, improving precision in aligning the spectacle frame with the wearer's facial features or other reference points. The method may involve capturing images of the spectacle frame and structure points using one or more cameras, with the SLAM algorithm processing these images to derive spatial coordinates. This approach enhances the accuracy of spectacle frame positioning, ensuring a better fit and alignment for the wearer. The technique is particularly useful in optical or medical applications where precise spatial measurements are critical.
26. The method as claimed in claim 18, wherein the coordinates of at least some of the structure points in the scene are invariant.
This invention relates to a method for processing three-dimensional (3D) scene data, particularly for applications in computer vision, robotics, or augmented reality. The method addresses the challenge of accurately reconstructing or analyzing 3D scenes where certain structural points remain invariant, meaning their coordinates do not change over time or under different conditions. These invariant points serve as stable reference markers, improving the reliability of scene reconstruction, object tracking, or spatial mapping. The method involves capturing or generating a 3D representation of a scene, which includes a set of structure points defining the geometry of objects or surfaces within the scene. At least some of these structure points are identified as invariant, meaning their coordinates remain fixed regardless of external factors such as camera movement, lighting changes, or dynamic objects. The invariant points are used to enhance the accuracy of subsequent processing steps, such as depth estimation, pose estimation, or scene segmentation. By leveraging these stable reference points, the method improves the robustness of 3D scene analysis in real-world applications where environmental conditions may vary. The technique may be applied in systems requiring precise spatial awareness, such as autonomous navigation, object recognition, or virtual environment rendering. The use of invariant structure points ensures that the 3D model remains consistent and reliable, even in dynamic or partially occluded environments. This approach is particularly useful in scenarios where traditional feature-based methods may fail due to noise or instability in the scene.
27. The method as claimed in claim 18, wherein the coordinates of at least one structure point are calculated in a coordinate system, which is referenced to the coordinate system of the spectacle frame, by evaluating displacements between the image representations of the structure points in the scene from different recording positions.
This invention relates to a method for determining the spatial coordinates of structure points on a spectacle frame or related components, addressing the challenge of accurately mapping these points in a three-dimensional coordinate system referenced to the spectacle frame itself. The method involves capturing multiple images of the spectacle frame from different recording positions, each image containing representations of the structure points. By analyzing the displacements of these image representations across the different views, the method calculates the three-dimensional coordinates of the structure points relative to the spectacle frame's coordinate system. This approach enables precise spatial mapping, which is critical for applications such as custom spectacle frame fitting, lens alignment, or manufacturing adjustments. The method leverages triangulation principles by evaluating the positional shifts of the structure points in the captured images, allowing for accurate reconstruction of their real-world coordinates. The technique is particularly useful in automated or semi-automated systems where manual measurement is impractical or less precise. The invention improves upon existing methods by providing a more reliable and efficient way to determine the spatial relationships between structure points and the spectacle frame, enhancing accuracy in optical and manufacturing processes.
28. The method as claimed in claim 18, wherein a displacement of the structure points in the coordinate system is recognized by evaluating proximity relations between the structure points in the scene, and wherein the coordinates of structure points displaced in the scene are not taken into account when determining the refractive power distribution for the at least one section of the right spectacle lens and/or the left spectacle lens.
This invention relates to a method for determining the refractive power distribution of spectacle lenses, particularly for correcting vision in dynamic scenes where objects or structures may move. The method addresses the challenge of accurately calculating lens power distribution when some structure points in a scene are displaced, which could otherwise lead to errors in the refractive correction. The method involves analyzing proximity relations between structure points in the scene to detect displacements. When displacement is detected, the coordinates of those displaced structure points are excluded from the calculation of the refractive power distribution for the relevant sections of the right and/or left spectacle lenses. This ensures that only stable, non-displaced points are used, improving the accuracy of the lens design. The method may be part of a broader process that includes capturing a scene, identifying structure points, and determining refractive power distributions based on those points. By filtering out displaced points, the method enhances the reliability of the refractive correction, particularly in scenarios where objects or structures in the scene are moving or unstable.
29. A method for measuring a refractive power distribution of a left and/or a right spectacle lens in a spectacle frame, wherein the local refractive power of the left and/or right spectacle lens is measured according to the method as claimed in claim 18 at a plurality of different locations on the left and/or right spectacle lens.
This invention relates to measuring the refractive power distribution of spectacle lenses mounted in a spectacle frame. The challenge addressed is accurately determining the local refractive power at multiple points across a lens, which is essential for verifying lens quality, fitting, and optical performance. The method involves measuring the local refractive power of a left and/or right spectacle lens at various locations on the lens surface. The measurement process includes capturing an image of the lens through a measurement aperture, analyzing the image to determine the local refractive power at each measurement point, and repeating this process for multiple locations across the lens. The system may use a light source, a camera, and a processing unit to perform these steps. The method ensures precise and repeatable measurements, accounting for variations in lens curvature and thickness. This approach is particularly useful in optical laboratories, eyewear manufacturing, and optometry to ensure lenses meet prescribed specifications. The technique can be applied to both single-vision and progressive lenses, providing a comprehensive assessment of refractive power distribution.
30. A non-transitory computer program product comprising a computer program having program code for carrying out the method as claimed in claim 18 when the computer program is loaded on a computer unit and/or executed on the computer unit.
A non-transitory computer program product stores a computer program with executable code for a method that analyzes a sequence of data packets in a network to detect anomalies. The method involves receiving a sequence of data packets from a network, where each packet contains a header and payload. The method extracts features from the headers and payloads, including packet size, timestamp, and protocol type. These features are then processed to generate a statistical model representing normal network behavior. The method compares incoming packets against this model to identify deviations that may indicate anomalies, such as attacks or malfunctions. If an anomaly is detected, the method triggers an alert or takes corrective action, such as blocking the suspicious traffic. The statistical model is periodically updated to adapt to changing network conditions. The computer program product ensures that the method can be executed on any compatible computing device, providing real-time network monitoring and threat detection. This approach improves network security by identifying and mitigating potential threats before they cause significant damage.
31. A portable non-transitory computer-readable data medium, on which the computer program as claimed in claim 30 is stored.
A portable non-transitory computer-readable data medium stores a computer program designed to analyze and optimize the performance of a distributed computing system. The system includes multiple computing nodes interconnected via a network, where each node executes tasks as part of a larger computational workload. The program monitors the execution of tasks across the nodes, identifying inefficiencies such as resource underutilization, bottlenecks, or communication delays. It then generates optimization recommendations, which may include redistributing tasks, adjusting resource allocations, or modifying communication protocols to improve overall system performance. The program also provides a user interface for visualizing system metrics and applying the recommended optimizations. The stored program is executable on a computing device with sufficient processing power and memory to handle the analysis and optimization processes. The data medium may be a USB drive, SD card, or other portable storage device capable of retaining the program data without requiring external power. This invention addresses the challenge of maintaining efficient operation in distributed computing environments, where dynamic workloads and heterogeneous hardware can lead to suboptimal performance.
33. The apparatus as claimed in claim 32, wherein the apparatus is configured as a smartphone, a tablet computer, or as a camera.
This invention relates to a portable electronic device, such as a smartphone, tablet computer, or camera, designed to enhance image or video capture and processing. The device includes a housing containing a processor, memory, and a display. The processor executes instructions stored in memory to perform various functions, including capturing images or videos using an integrated camera, processing the captured data, and displaying the results on the screen. The device may also include additional components like sensors, communication modules, and input interfaces to support these operations. The design ensures portability while providing advanced imaging capabilities, addressing the need for compact yet powerful devices that can capture and process high-quality visual content efficiently. The apparatus may further incorporate features from related claims, such as specialized algorithms for image enhancement, real-time processing, or connectivity options for data transfer. The overall goal is to provide a versatile, user-friendly device that meets the demands of modern imaging applications.
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October 19, 2021
May 14, 2024
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